Frugivores visits
Figure 1. Meles meles tracks in “sandtramp” beneath a C. humilis infructesence.
Step 1. Open Martinazo and Matasgordas matrix
Opening a matrix file with weighted visits of frugivores in individual plants, the “row.names=1” is necessary to run the model and to detect the “name of plants” in the matrix. Note: visit frequency= animal-visit-days/total-survey days.
#Martinazo
mart<-read.csv("~/Desktop/Palmito/Postdoc-Interaction Networks/mart_visit.csv",header=TRUE,check.names=FALSE,row.names=1)
#Matasgordas
matas<-read.csv("~/Desktop/Palmito/Postdoc-Interaction Networks/matas_visit.csv",header=TRUE,check.names=FALSE,row.names=1)
Step 2. Using “bipartite” package
library(bipartite)Step 2.1. Ploting the web.
Creates a bipartite network were the high level will be represented by the frugivores and low level to each individual plant. Plants arrengement represents the aggregation level from high-low aggregation. This was obtained through Dirilichet tesselations, where plants haighly aggregated were those with the less area without any other dwarf palm. 1
Step 3. Calculate different indexes of a network.
Closeness scores for nodes in a weighted network based on the distance_w-function.
Betweenness scores for nodes in a weighted network based on the distance_w-function.
Species level describe a species’ degree as sum of its links.
Link level computes the contribution of each species to the overall nestedness.
## Warning in as.tnet(net, type = "weighted one-mode tnet"): There were self-
## loops in the edgelist, these were removed
## Warning in as.tnet(net, type = "weighted one-mode tnet"): There were self-
## loops in the edgelist, these were removed## This function is SLOW!
## Monitor your system's activity; depending on steps-setting this may take minutes to hours!
##
## identifyModules: start building legal dendrogram
##
## #steps M best M temperature
## [1016] 0.0176224 (-2.06866e-16) 1e-05
##
## identifyModules: building of legal dendrogram finished
## identifyModules: start finding best dendrogram
##
## [1016] 0.0176224 (0.0176224) 1e-05
## [10000] 0.0257446 (0.0257446) 9.95804e-06
## [20000] 0.240315 (0.240315) 9.99552e-06
## [30000] 0.267135 (0.267135) 9.92285e-06
## [40000] 0.282473 (0.282473) 9.95486e-06
## [50000] 0.284198 (0.284198) 9.94546e-06
## [60000] 0.284198 (0.284198) 9.84567e-06
## [70000] 0.284198 (0.284198) 9.74587e-06
## [80000] 0.284198 (0.284198) 9.64607e-06
## [90000] 0.284198 (0.284198) 9.54627e-06
## [93222] 0.284198 (0.284198) 9.51412e-06
## [100000] 0.284198 (0.284198) 9.44648e-06
## [110000] 0.284198 (0.284198) 9.34668e-06
## [120000] 0.284198 (0.284198) 9.24688e-06
## [130000] 0.284198 (0.284198) 9.14709e-06
## [140000] 0.284198 (0.284198) 9.04729e-06
## [150000] 0.284198 (0.284198) 8.94749e-06
## [160000] 0.284198 (0.284198) 8.84769e-06
## [170000] 0.284198 (0.284198) 8.7479e-06
## [180000] 0.284198 (0.284198) 8.6481e-06
## [190000] 0.284198 (0.284198) 8.5483e-06
## [200000] 0.284198 (0.284198) 8.4485e-06
## [210000] 0.284198 (0.284198) 8.34871e-06
## [220000] 0.284198 (0.284198) 8.24891e-06
## [230000] 0.284198 (0.284198) 8.14911e-06
## [240000] 0.284198 (0.284198) 8.04931e-06
## [250000] 0.284198 (0.284198) 7.94952e-06
## [260000] 0.284198 (0.284198) 7.84972e-06
## [270000] 0.284198 (0.284198) 7.74992e-06
## [280000] 0.284198 (0.284198) 7.65012e-06
## [290000] 0.284198 (0.284198) 7.55033e-06
## [300000] 0.284198 (0.284198) 7.45053e-06
## [310000] 0.284198 (0.284198) 7.35073e-06
## [320000] 0.284198 (0.284198) 7.25093e-06
## [330000] 0.284198 (0.284198) 7.15114e-06
## [340000] 0.284198 (0.284198) 7.05134e-06
## [350000] 0.284198 (0.284198) 6.95154e-06
## [360000] 0.284198 (0.284198) 6.85174e-06
## [370000] 0.284198 (0.284198) 6.75195e-06
## [380000] 0.284198 (0.284198) 6.65215e-06
## [390000] 0.284198 (0.284198) 6.55235e-06
## [400000] 0.284198 (0.284198) 6.45255e-06
## [410000] 0.284198 (0.284198) 6.35276e-06
## [420000] 0.284198 (0.284198) 6.25296e-06
## [430000] 0.284198 (0.284198) 6.15316e-06
## [440000] 0.284198 (0.284198) 6.05336e-06
## [445608] 0.284198 (0.284198) 5.9974e-06
## [450000] 0.284198 (0.284198) 5.95357e-06
## [460000] 0.284198 (0.284198) 5.85377e-06
## [470000] 0.284198 (0.284198) 5.75397e-06
## [480000] 0.284198 (0.284198) 5.65417e-06
## [490000] 0.284198 (0.284198) 5.55438e-06
## [500000] 0.284198 (0.284198) 5.45458e-06
## [510000] 0.284198 (0.284198) 5.35478e-06
## [520000] 0.284198 (0.284198) 5.25498e-06
## [530000] 0.284198 (0.284198) 5.15519e-06
## [540000] 0.284198 (0.284198) 5.05539e-06
## [550000] 0.284198 (0.284198) 4.95559e-06
## [560000] 0.284198 (0.284198) 4.85579e-06
## [570000] 0.284198 (0.284198) 4.756e-06
## [580000] 0.284198 (0.284198) 4.6562e-06
## [590000] 0.284198 (0.284198) 4.5564e-06
## [600000] 0.284198 (0.284198) 4.4566e-06
## [610000] 0.284198 (0.284198) 4.35681e-06
## [620000] 0.284198 (0.284198) 4.25701e-06
## [630000] 0.284198 (0.284198) 4.15721e-06
## [640000] 0.284198 (0.284198) 4.05742e-06
## [650000] 0.284198 (0.284198) 3.95762e-06
## [660000] 0.284198 (0.284198) 3.85782e-06
## [670000] 0.284198 (0.284198) 3.75802e-06
## [680000] 0.284198 (0.284198) 3.65823e-06
## [690000] 0.284198 (0.284198) 3.55843e-06
## [700000] 0.284198 (0.284198) 3.45863e-06
## [710000] 0.284198 (0.284198) 3.35883e-06
## [720000] 0.284198 (0.284198) 3.25904e-06
## [730000] 0.284198 (0.284198) 3.15924e-06
## [740000] 0.284198 (0.284198) 3.05944e-06
## [750000] 0.284198 (0.284198) 2.95964e-06
## [760000] 0.284198 (0.284198) 2.85985e-06
## [769400] 0.284198 (0.284198) 2.76604e-06
## [770000] 0.284198 (0.284198) 2.76005e-06
## [780000] 0.284198 (0.284198) 2.66025e-06
## [790000] 0.284198 (0.284198) 2.56045e-06
## [800000] 0.284198 (0.284198) 2.46066e-06
## [810000] 0.284198 (0.284198) 2.36086e-06
## [820000] 0.284198 (0.284198) 2.26106e-06
## [830000] 0.284198 (0.284198) 2.16126e-06
## [840000] 0.284198 (0.284198) 2.06147e-06
## [850000] 0.284198 (0.284198) 1.96167e-06
## [860000] 0.284198 (0.284198) 1.86187e-06
## [870000] 0.284198 (0.284198) 1.76207e-06
## [880000] 0.284198 (0.284198) 1.66228e-06
## [890000] 0.284198 (0.284198) 1.56248e-06
## [900000] 0.284198 (0.284198) 1.46268e-06
## [910000] 0.284198 (0.284198) 1.36288e-06
## [920000] 0.284198 (0.284198) 1.26309e-06
## [930000] 0.284198 (0.284198) 1.16329e-06
## [940000] 0.284198 (0.284198) 1.06349e-06
## [950000] 0.284198 (0.284198) 9.63694e-07
## [960000] 0.284198 (0.284198) 8.63897e-07
## [970000] 0.284198 (0.284198) 7.64099e-07
## [980000] 0.284198 (0.284198) 6.64302e-07
## [990000] 0.284198 (0.284198) 5.64504e-07
## [1000000] 0.284198 (0.284198) 4.64707e-07
## [1010000] 0.284198 (0.284198) 3.64909e-07
## [1020000] 0.284198 (0.284198) 2.65112e-07
## [1030000] 0.284198 (0.284198) 1.65314e-07
## [1040000] 0.284198 (0.284198) 6.5517e-08
## [1050000] 0.284198 (0.284198) 9.97962e-12
##
## identifyModules: finding best dendrogram complete
##
## identifyModules: modularity = 0.284198## This function is SLOW!
## Monitor your system's activity; depending on steps-setting this may take minutes to hours!
##
## identifyModules: start building legal dendrogram
##
## #steps M best M temperature
## [10000] -47.9832 (-47.9832) 1e-05
## [20000] -8.06976e-16 (-5.7067e-16) 1e-05
## [30000] -1.0087e-15 (-5.7067e-16) 1e-05
## [33411] -1.03031e-15 (-5.7067e-16) 1e-05
## [39488] 0.00741797 (-5.7067e-16) 1e-05
##
## identifyModules: building of legal dendrogram finished
## identifyModules: start finding best dendrogram
##
## [39488] 0.00741797 (0.00741797) 9.98392e-06
## [40000] 0.00741797 (0.00741797) 9.97881e-06
## [50000] 0.0476313 (0.0476313) 9.9302e-06
## [60000] 0.0544581 (0.0544581) 9.91877e-06
## [70000] 0.0544581 (0.0544581) 9.81882e-06
## [80000] 0.0544581 (0.0544581) 9.71886e-06
## [90000] 0.069576 (0.069576) 9.95186e-06
## [100000] 0.069576 (0.069576) 9.85217e-06
## [110000] 0.069576 (0.069576) 9.75248e-06
## [120000] 0.0762916 (0.0762916) 9.93387e-06
## [130000] 0.0762916 (0.0762916) 9.83416e-06
## [140000] 0.18954 (0.18954) 9.95882e-06
## [150000] 0.208527 (0.208527) 9.96025e-06
## [160000] 0.21134 (0.21134) 9.92591e-06
## [165159] 0.272956 (0.272956) 9.98972e-06
## [170000] 0.272956 (0.272956) 9.94136e-06
## [180000] 0.272956 (0.272956) 9.84146e-06
## [190000] 0.275769 (0.275769) 9.91323e-06
## [200000] 0.275769 (0.275769) 9.81327e-06
## [210000] 0.275769 (0.275769) 9.71331e-06
## [220000] 0.340263 (0.340263) 9.9536e-06
## [230000] 0.354702 (0.354702) 9.91666e-06
## [240000] 0.362083 (0.362083) 9.9014e-06
## [250000] 0.362083 (0.362083) 9.80143e-06
## [260000] 0.365619 (0.365619) 9.93917e-06
## [270000] 0.365619 (0.365619) 9.83932e-06
## [280000] 0.365619 (0.365619) 9.73946e-06
## [290000] 0.365619 (0.365619) 9.63961e-06
## [300000] 0.365619 (0.365619) 9.53975e-06
## [310000] 0.365619 (0.365619) 9.4399e-06
## [320000] 0.365619 (0.365619) 9.34005e-06
## [330000] 0.365619 (0.365619) 9.24019e-06
## [340000] 0.365619 (0.365619) 9.14034e-06
## [350000] 0.365619 (0.365619) 9.04048e-06
## [360000] 0.365619 (0.365619) 8.94063e-06
## [370000] 0.365619 (0.365619) 8.84078e-06
## [380000] 0.365619 (0.365619) 8.74092e-06
## [390000] 0.365619 (0.365619) 8.64107e-06
## [400000] 0.365619 (0.365619) 8.54121e-06
## [410000] 0.365619 (0.365619) 8.44136e-06
## [417122] 0.365619 (0.365619) 8.37024e-06
## [420000] 0.365619 (0.365619) 8.3415e-06
## [430000] 0.365619 (0.365619) 8.24165e-06
## [440000] 0.365619 (0.365619) 8.1418e-06
## [450000] 0.365619 (0.365619) 8.04194e-06
## [460000] 0.365619 (0.365619) 7.94209e-06
## [470000] 0.365619 (0.365619) 7.84223e-06
## [480000] 0.365619 (0.365619) 7.74238e-06
## [490000] 0.365619 (0.365619) 7.64252e-06
## [500000] 0.365619 (0.365619) 7.54267e-06
## [510000] 0.365619 (0.365619) 7.44282e-06
## [520000] 0.365619 (0.365619) 7.34296e-06
## [530000] 0.365619 (0.365619) 7.24311e-06
## [540000] 0.365619 (0.365619) 7.14325e-06
## [550000] 0.365619 (0.365619) 7.0434e-06
## [560000] 0.365619 (0.365619) 6.94354e-06
## [570000] 0.365619 (0.365619) 6.84369e-06
## [580000] 0.365619 (0.365619) 6.74384e-06
## [590000] 0.365619 (0.365619) 6.64398e-06
## [600000] 0.365619 (0.365619) 6.54413e-06
## [610000] 0.365619 (0.365619) 6.44427e-06
## [620000] 0.365619 (0.365619) 6.34442e-06
## [630000] 0.365619 (0.365619) 6.24456e-06
## [640000] 0.365619 (0.365619) 6.14471e-06
## [650000] 0.365619 (0.365619) 6.04486e-06
## [660000] 0.365619 (0.365619) 5.945e-06
## [670000] 0.365619 (0.365619) 5.84515e-06
## [680000] 0.365619 (0.365619) 5.74529e-06
## [690000] 0.365619 (0.365619) 5.64544e-06
## [700000] 0.365619 (0.365619) 5.54559e-06
## [710000] 0.365619 (0.365619) 5.44573e-06
## [720000] 0.365619 (0.365619) 5.34588e-06
## [730000] 0.365619 (0.365619) 5.24602e-06
## [734494] 0.365619 (0.365619) 5.20115e-06
## [740000] 0.365619 (0.365619) 5.14617e-06
## [750000] 0.365619 (0.365619) 5.04631e-06
## [760000] 0.365619 (0.365619) 4.94646e-06
## [770000] 0.365619 (0.365619) 4.84661e-06
## [780000] 0.365619 (0.365619) 4.74675e-06
## [790000] 0.365619 (0.365619) 4.6469e-06
## [800000] 0.365619 (0.365619) 4.54704e-06
## [810000] 0.365619 (0.365619) 4.44719e-06
## [820000] 0.365619 (0.365619) 4.34733e-06
## [830000] 0.365619 (0.365619) 4.24748e-06
## [840000] 0.365619 (0.365619) 4.14763e-06
## [850000] 0.365619 (0.365619) 4.04777e-06
## [860000] 0.365619 (0.365619) 3.94792e-06
## [870000] 0.365619 (0.365619) 3.84806e-06
## [880000] 0.365619 (0.365619) 3.74821e-06
## [890000] 0.365619 (0.365619) 3.64835e-06
## [900000] 0.365619 (0.365619) 3.5485e-06
## [910000] 0.365619 (0.365619) 3.44865e-06
## [920000] 0.365619 (0.365619) 3.34879e-06
## [930000] 0.365619 (0.365619) 3.24894e-06
## [940000] 0.365619 (0.365619) 3.14908e-06
## [950000] 0.365619 (0.365619) 3.04923e-06
## [960000] 0.365619 (0.365619) 2.94937e-06
## [970000] 0.365619 (0.365619) 2.84952e-06
## [980000] 0.365619 (0.365619) 2.74967e-06
## [990000] 0.365619 (0.365619) 2.64981e-06
## [1000000] 0.365619 (0.365619) 2.54996e-06
## [1010000] 0.365619 (0.365619) 2.4501e-06
## [1020000] 0.365619 (0.365619) 2.35025e-06
## [1030000] 0.365619 (0.365619) 2.2504e-06
## [1034639] 0.365619 (0.365619) 2.20407e-06
## [1040000] 0.365619 (0.365619) 2.15054e-06
## [1050000] 0.365619 (0.365619) 2.05069e-06
## [1060000] 0.365619 (0.365619) 1.95083e-06
## [1070000] 0.365619 (0.365619) 1.85098e-06
## [1080000] 0.365619 (0.365619) 1.75112e-06
## [1090000] 0.365619 (0.365619) 1.65127e-06
## [1100000] 0.365619 (0.365619) 1.55142e-06
## [1110000] 0.365619 (0.365619) 1.45156e-06
## [1120000] 0.365619 (0.365619) 1.35171e-06
## [1130000] 0.365619 (0.365619) 1.25185e-06
## [1140000] 0.365619 (0.365619) 1.152e-06
## [1150000] 0.365619 (0.365619) 1.05214e-06
## [1160000] 0.365619 (0.365619) 9.5229e-07
## [1170000] 0.365619 (0.365619) 8.52436e-07
## [1180000] 0.365619 (0.365619) 7.52581e-07
## [1190000] 0.365619 (0.365619) 6.52727e-07
## [1200000] 0.365619 (0.365619) 5.52873e-07
## [1210000] 0.365619 (0.365619) 4.53019e-07
## [1220000] 0.365619 (0.365619) 3.53164e-07
## [1230000] 0.365619 (0.365619) 2.5331e-07
## [1240000] 0.365619 (0.365619) 1.53456e-07
## [1247177] 0.365619 (0.365619) 8.17906e-08
## [1250000] 0.365619 (0.365619) 5.36018e-08
## [1260000] 0.365619 (0.365619) 9.98534e-12
##
## identifyModules: finding best dendrogram complete
##
## identifyModules: modularity = 0.365619
Coping the results to my folder in local repository
write.table(clos_mart, "/Users/apple/Desktop/Palmito/Postdoc-Interaction Networks/Dispersal Networks/clos_mart.txt", sep="\t")Fruit remotion rates
Figure 2. Wildboar feeding on C. humilis fruits
Step 1. Open Martinazo and Matasgordas matrix
Opening a matrix file with weighted links with frugivores fruit remotion in individual plants. Other specifications of the matrix are described in the previous section.
#Martinazo
mart_f<-read.csv("~/Desktop/Palmito/Postdoc-Interaction Networks/mart_fruits.csv",header=TRUE,check.names=FALSE,row.names=1)
#Matasgordas
matas_f<-read.csv("~/Desktop/Palmito/Postdoc-Interaction Networks/matas_fruits.csv",header=TRUE,check.names=FALSE,row.names=1)
Step 2. Using “bipartite” package
library(biparite)
Step 2.1. Ploting the web.
Creates a bipartite network were the high level will be represented by the frugivores and low level to each individual plant. Links are weigthed with the proportion fruit remotion proportion/animal/individual plant.2
Step 3. Calculate different indexes of a network.3
Closeness
Betweenness
Species level
Link level
## This function is SLOW!
## Monitor your system's activity; depending on steps-setting this may take minutes to hours!
##
## identifyModules: start building legal dendrogram
##
## #steps M best M temperature
## [3738] 1.52005e-16 (-13.2803) 1e-05
##
## identifyModules: building of legal dendrogram finished
## identifyModules: start finding best dendrogram
##
## [3738] 1.52005e-16 (1.52005e-16) 9.99338e-06
## [10000] 0.103459 (0.103459) 9.96394e-06
## [20000] 0.200954 (0.200954) 9.94433e-06
## [30000] 0.203494 (0.203494) 9.88669e-06
## [40000] 0.203494 (0.203494) 9.78707e-06
## [50000] 0.203494 (0.203494) 9.68744e-06
## [60000] 0.203494 (0.203494) 9.58782e-06
## [70000] 0.450592 (0.450592) 9.94106e-06
## [80000] 0.450592 (0.450592) 9.84143e-06
## [90000] 0.450592 (0.450592) 9.74181e-06
## [100000] 0.450592 (0.450592) 9.64218e-06
## [110000] 0.450592 (0.450592) 9.54255e-06
## [120000] 0.450592 (0.450592) 9.44293e-06
## [130000] 0.450592 (0.450592) 9.3433e-06
## [140000] 0.450592 (0.450592) 9.24367e-06
## [150000] 0.450592 (0.450592) 9.14405e-06
## [160000] 0.450592 (0.450592) 9.04442e-06
## [170000] 0.450592 (0.450592) 8.9448e-06
## [180000] 0.450592 (0.450592) 8.84517e-06
## [190000] 0.450592 (0.450592) 8.74554e-06
## [200000] 0.450592 (0.450592) 8.64592e-06
## [210000] 0.450592 (0.450592) 8.54629e-06
## [220000] 0.450592 (0.450592) 8.44667e-06
## [230000] 0.450592 (0.450592) 8.34704e-06
## [240000] 0.450592 (0.450592) 8.24741e-06
## [250000] 0.450592 (0.450592) 8.14779e-06
## [260000] 0.450592 (0.450592) 8.04816e-06
## [262747] 0.450592 (0.450592) 8.02079e-06
## [270000] 0.450592 (0.450592) 7.94853e-06
## [280000] 0.450592 (0.450592) 7.84891e-06
## [290000] 0.450592 (0.450592) 7.74928e-06
## [300000] 0.450592 (0.450592) 7.64966e-06
## [310000] 0.450592 (0.450592) 7.55003e-06
## [320000] 0.450592 (0.450592) 7.4504e-06
## [330000] 0.450592 (0.450592) 7.35078e-06
## [340000] 0.450592 (0.450592) 7.25115e-06
## [350000] 0.450592 (0.450592) 7.15153e-06
## [360000] 0.450592 (0.450592) 7.0519e-06
## [370000] 0.450592 (0.450592) 6.95227e-06
## [380000] 0.450592 (0.450592) 6.85265e-06
## [390000] 0.450592 (0.450592) 6.75302e-06
## [400000] 0.450592 (0.450592) 6.65339e-06
## [410000] 0.450592 (0.450592) 6.55377e-06
## [420000] 0.450592 (0.450592) 6.45414e-06
## [430000] 0.450592 (0.450592) 6.35452e-06
## [440000] 0.450592 (0.450592) 6.25489e-06
## [450000] 0.450592 (0.450592) 6.15526e-06
## [460000] 0.450592 (0.450592) 6.05564e-06
## [470000] 0.450592 (0.450592) 5.95601e-06
## [480000] 0.450592 (0.450592) 5.85639e-06
## [490000] 0.450592 (0.450592) 5.75676e-06
## [500000] 0.450592 (0.450592) 5.65713e-06
## [510000] 0.450592 (0.450592) 5.55751e-06
## [520000] 0.450592 (0.450592) 5.45788e-06
## [530000] 0.450592 (0.450592) 5.35825e-06
## [540000] 0.450592 (0.450592) 5.25863e-06
## [550000] 0.450592 (0.450592) 5.159e-06
## [560000] 0.450592 (0.450592) 5.05938e-06
## [570000] 0.450592 (0.450592) 4.95975e-06
## [580000] 0.450592 (0.450592) 4.86012e-06
## [585570] 0.450592 (0.450592) 4.80463e-06
## [590000] 0.450592 (0.450592) 4.7605e-06
## [600000] 0.450592 (0.450592) 4.66087e-06
## [610000] 0.450592 (0.450592) 4.56124e-06
## [620000] 0.450592 (0.450592) 4.46162e-06
## [630000] 0.450592 (0.450592) 4.36199e-06
## [640000] 0.450592 (0.450592) 4.26237e-06
## [650000] 0.450592 (0.450592) 4.16274e-06
## [660000] 0.450592 (0.450592) 4.06311e-06
## [670000] 0.450592 (0.450592) 3.96349e-06
## [680000] 0.450592 (0.450592) 3.86386e-06
## [690000] 0.450592 (0.450592) 3.76424e-06
## [700000] 0.450592 (0.450592) 3.66461e-06
## [710000] 0.450592 (0.450592) 3.56498e-06
## [720000] 0.450592 (0.450592) 3.46536e-06
## [730000] 0.450592 (0.450592) 3.36573e-06
## [740000] 0.450592 (0.450592) 3.2661e-06
## [750000] 0.450592 (0.450592) 3.16648e-06
## [760000] 0.450592 (0.450592) 3.06685e-06
## [770000] 0.450592 (0.450592) 2.96723e-06
## [780000] 0.450592 (0.450592) 2.8676e-06
## [790000] 0.450592 (0.450592) 2.76797e-06
## [800000] 0.450592 (0.450592) 2.66835e-06
## [810000] 0.450592 (0.450592) 2.56872e-06
## [820000] 0.450592 (0.450592) 2.4691e-06
## [830000] 0.450592 (0.450592) 2.36947e-06
## [840000] 0.450592 (0.450592) 2.26984e-06
## [850000] 0.450592 (0.450592) 2.17022e-06
## [860000] 0.450592 (0.450592) 2.07059e-06
## [870000] 0.450592 (0.450592) 1.97096e-06
## [880000] 0.450592 (0.450592) 1.87134e-06
## [890000] 0.450592 (0.450592) 1.77171e-06
## [900000] 0.450592 (0.450592) 1.67209e-06
## [910000] 0.450592 (0.450592) 1.57246e-06
## [920000] 0.450592 (0.450592) 1.47283e-06
## [930000] 0.450592 (0.450592) 1.37321e-06
## [940000] 0.450592 (0.450592) 1.27358e-06
## [950000] 0.450592 (0.450592) 1.17395e-06
## [959167] 0.450592 (0.450592) 1.08263e-06
## [960000] 0.450592 (0.450592) 1.07433e-06
## [970000] 0.450592 (0.450592) 9.74703e-07
## [980000] 0.450592 (0.450592) 8.75076e-07
## [990000] 0.450592 (0.450592) 7.7545e-07
## [1000000] 0.450592 (0.450592) 6.75824e-07
## [1010000] 0.450592 (0.450592) 5.76198e-07
## [1020000] 0.450592 (0.450592) 4.76572e-07
## [1030000] 0.450592 (0.450592) 3.76946e-07
## [1040000] 0.450592 (0.450592) 2.77319e-07
## [1050000] 0.450592 (0.450592) 1.77693e-07
## [1060000] 0.450592 (0.450592) 7.80671e-08
## [1070000] 0.450592 (0.450592) 8.99335e-17
##
## identifyModules: finding best dendrogram complete
##
## identifyModules: modularity = 0.450592## Warning in as.tnet(net, type = "weighted one-mode tnet"): There were self-
## loops in the edgelist, these were removed
## Warning in as.tnet(net, type = "weighted one-mode tnet"): There were self-
## loops in the edgelist, these were removed## This function is SLOW!
## Monitor your system's activity; depending on steps-setting this may take minutes to hours!
##
## identifyModules: start building legal dendrogram
##
## #steps M best M temperature
## [2789] 0.118098 (-19.8825) 1e-05
##
## identifyModules: building of legal dendrogram finished
## identifyModules: start finding best dendrogram
##
## [2789] 0.118098 (0.118098) 9.99498e-06
## [10000] 0.186527 (0.186527) 9.94492e-06
## [20000] 0.186806 (0.186806) 9.92008e-06
## [26501] 0.256627 (0.256627) 9.96829e-06
## [30000] 0.259395 (0.259395) 9.9788e-06
## [40000] 0.259395 (0.259395) 9.87881e-06
## [50000] 0.259395 (0.259395) 9.77881e-06
## [60000] 0.272373 (0.272373) 9.91845e-06
## [70000] 0.272373 (0.272373) 9.81901e-06
## [80000] 0.326501 (0.326501) 9.93573e-06
## [90000] 0.326501 (0.326501) 9.83616e-06
## [100000] 0.333754 (0.333754) 9.90239e-06
## [110000] 0.358014 (0.358014) 9.95246e-06
## [120000] 0.36687 (0.36687) 9.90931e-06
## [130000] 0.36687 (0.36687) 9.80932e-06
## [140000] 0.36687 (0.36687) 9.70933e-06
## [150000] 0.36687 (0.36687) 9.60934e-06
## [160000] 0.36687 (0.36687) 9.50934e-06
## [170000] 0.36687 (0.36687) 9.40935e-06
## [180000] 0.36687 (0.36687) 9.30936e-06
## [190000] 0.36687 (0.36687) 9.20937e-06
## [200000] 0.36687 (0.36687) 9.10937e-06
## [210000] 0.36687 (0.36687) 9.00938e-06
## [220000] 0.36687 (0.36687) 8.90939e-06
## [230000] 0.36687 (0.36687) 8.8094e-06
## [240000] 0.36687 (0.36687) 8.7094e-06
## [250000] 0.36687 (0.36687) 8.60941e-06
## [260000] 0.36687 (0.36687) 8.50942e-06
## [270000] 0.36687 (0.36687) 8.40943e-06
## [280000] 0.36687 (0.36687) 8.30944e-06
## [290000] 0.36687 (0.36687) 8.20944e-06
## [300000] 0.36687 (0.36687) 8.10945e-06
## [306776] 0.36687 (0.36687) 8.0417e-06
## [310000] 0.36687 (0.36687) 8.00946e-06
## [320000] 0.36687 (0.36687) 7.90947e-06
## [330000] 0.36687 (0.36687) 7.80947e-06
## [340000] 0.36687 (0.36687) 7.70948e-06
## [350000] 0.36687 (0.36687) 7.60949e-06
## [360000] 0.36687 (0.36687) 7.5095e-06
## [370000] 0.36687 (0.36687) 7.4095e-06
## [380000] 0.36687 (0.36687) 7.30951e-06
## [390000] 0.36687 (0.36687) 7.20952e-06
## [400000] 0.36687 (0.36687) 7.10953e-06
## [410000] 0.36687 (0.36687) 7.00953e-06
## [420000] 0.36687 (0.36687) 6.90954e-06
## [430000] 0.36687 (0.36687) 6.80955e-06
## [440000] 0.36687 (0.36687) 6.70956e-06
## [450000] 0.36687 (0.36687) 6.60957e-06
## [460000] 0.36687 (0.36687) 6.50957e-06
## [470000] 0.36687 (0.36687) 6.40958e-06
## [480000] 0.36687 (0.36687) 6.30959e-06
## [490000] 0.36687 (0.36687) 6.2096e-06
## [500000] 0.36687 (0.36687) 6.1096e-06
## [510000] 0.36687 (0.36687) 6.00961e-06
## [520000] 0.36687 (0.36687) 5.90962e-06
## [530000] 0.36687 (0.36687) 5.80963e-06
## [540000] 0.36687 (0.36687) 5.70963e-06
## [550000] 0.36687 (0.36687) 5.60964e-06
## [560000] 0.36687 (0.36687) 5.50965e-06
## [570000] 0.36687 (0.36687) 5.40966e-06
## [580000] 0.36687 (0.36687) 5.30966e-06
## [590000] 0.36687 (0.36687) 5.20967e-06
## [600000] 0.36687 (0.36687) 5.10968e-06
## [610000] 0.36687 (0.36687) 5.00969e-06
## [620000] 0.36687 (0.36687) 4.9097e-06
## [630000] 0.36687 (0.36687) 4.8097e-06
## [640000] 0.36687 (0.36687) 4.70971e-06
## [645832] 0.36687 (0.36687) 4.65139e-06
## [650000] 0.36687 (0.36687) 4.60972e-06
## [660000] 0.36687 (0.36687) 4.50973e-06
## [670000] 0.36687 (0.36687) 4.40973e-06
## [680000] 0.36687 (0.36687) 4.30974e-06
## [690000] 0.36687 (0.36687) 4.20975e-06
## [700000] 0.36687 (0.36687) 4.10976e-06
## [710000] 0.36687 (0.36687) 4.00976e-06
## [720000] 0.36687 (0.36687) 3.90977e-06
## [730000] 0.36687 (0.36687) 3.80978e-06
## [740000] 0.36687 (0.36687) 3.70979e-06
## [750000] 0.36687 (0.36687) 3.60979e-06
## [760000] 0.36687 (0.36687) 3.5098e-06
## [770000] 0.36687 (0.36687) 3.40981e-06
## [780000] 0.36687 (0.36687) 3.30982e-06
## [790000] 0.36687 (0.36687) 3.20982e-06
## [800000] 0.36687 (0.36687) 3.10983e-06
## [810000] 0.36687 (0.36687) 3.00984e-06
## [820000] 0.36687 (0.36687) 2.90985e-06
## [830000] 0.36687 (0.36687) 2.80986e-06
## [840000] 0.36687 (0.36687) 2.70986e-06
## [850000] 0.36687 (0.36687) 2.60987e-06
## [860000] 0.36687 (0.36687) 2.50988e-06
## [870000] 0.36687 (0.36687) 2.40989e-06
## [880000] 0.36687 (0.36687) 2.30989e-06
## [890000] 0.36687 (0.36687) 2.2099e-06
## [900000] 0.36687 (0.36687) 2.10991e-06
## [910000] 0.36687 (0.36687) 2.00992e-06
## [920000] 0.36687 (0.36687) 1.90992e-06
## [930000] 0.36687 (0.36687) 1.80993e-06
## [940000] 0.36687 (0.36687) 1.70994e-06
## [950000] 0.36687 (0.36687) 1.60995e-06
## [960000] 0.36687 (0.36687) 1.50995e-06
## [970000] 0.36687 (0.36687) 1.40996e-06
## [980000] 0.36687 (0.36687) 1.30997e-06
## [990000] 0.36687 (0.36687) 1.20998e-06
## [996440] 0.36687 (0.36687) 1.14558e-06
## [1000000] 0.36687 (0.36687) 1.10999e-06
## [1010000] 0.36687 (0.36687) 1.00999e-06
## [1020000] 0.36687 (0.36687) 9.10001e-07
## [1030000] 0.36687 (0.36687) 8.10008e-07
## [1040000] 0.36687 (0.36687) 7.10016e-07
## [1050000] 0.36687 (0.36687) 6.10023e-07
## [1060000] 0.36687 (0.36687) 5.10031e-07
## [1070000] 0.36687 (0.36687) 4.10039e-07
## [1080000] 0.36687 (0.36687) 3.10046e-07
## [1090000] 0.36687 (0.36687) 2.10054e-07
## [1100000] 0.36687 (0.36687) 1.10062e-07
## [1110000] 0.36687 (0.36687) 1.00692e-08
## [1120000] 0.36687 (0.36687) 9.99909e-12
##
## identifyModules: finding best dendrogram complete
##
## identifyModules: modularity = 0.36687
Step 3.1. Ploting modules in the networks
Step 4. Gathering Martinazo and Matasgordas’ matrixs as one; plants are ordered from more to less aggregated
Step 5. Changing the matrix by eliminating unknown visitors
#Martinazo
mart_fnun<-read.csv("~/Desktop/Palmito/Postdoc-Interaction Networks/mart_fruits_no_unk.csv",header=TRUE,check.names=FALSE,row.names=1)
#Matasgordas
matas_fnun<-read.csv("~/Desktop/Palmito/Postdoc-Interaction Networks/matas_fruits_no_unk.csv",header=TRUE,check.names=FALSE,row.names=1)
Bipartite plot
Notice: Plants colors in gray scale [col.low=c(gray(seq(0.1,1,length=24)))], goes from black (aggregated plants) to white (more isolated), length refers to the number of plants in the plot. In High level, different colors in “col.high” means different guilds: white=predators, dark gray=defleshers, black=dispersers and light gray=unknow.↩
For more information see previous analysis↩
For more information see previous analysis↩